The informed neuron: Issues in the use of information theory in the behavioral sciences

The concept of information is virtually ubiquitous in contemporary cognitive science. It is claimed to be processed (in cognitivist theories of perception and comprehension), stored (in cognitivist theories of memory and recognition), and otherwise manipulated and transformed by the human central nervous system. Fred Dretske's extensive philosophical defense of a theory of informational content (semantic information) based upon the Shannon-Weaver formal theory of information is subjected to critical scrutiny. A major difficulty is identified in Dretske's equivocations in the use of the concept of a signal bearing informational content. Gibson's alternative conception of information (construed as analog by Dretske), while avoiding many of the problems located in the conventional use of signal, raises different but equally serious questions. It is proposed that, taken literally, the human CNS does not extract or process information at all; rather, whatever information is construed as locatable in the CNS is information only for an observer-theorist and only for certain purposes.Blood courses through our veins, andinformation through our central nervous system.— A Neuropsychology Textbook.     

Über die Konvergenz des Relaxationsverfahrens bei nicht-negativen und diagonaldominanten Matrizen

Zusammenfassung In der folgenden Arbeit werden zunächst die Begriffe Gesamtschrittverfahren, Einzelschrittverfahren und Relaxationsverfahren allgemein formuliert und dann auf allgemeine lineare Gleichungssysteme angewandt. Im Spezialfall einer Matrix mit verschwindender Hauptdiagonale erhält man so die bekanntenJacobi-, Gauss-Seidel- und Relaxationsverfahren. Satz 1 macht eine Aussage über die Konvergenz des Einzelschrittverfahrens bei allgemeinen, nicht-negativen Matrizen. Der Beweis verläuft ähnlich wie in einem bereits 1948 vonStein undRosenberg [2] behandelten Spezialfall. Als Korollar ergibt sich eine Aussage über die Konvergenz des Relaxationsverfahrens bei nicht-negativen Matrizen. Es wird ferner der Satz 2 über die Konvergenz des Relaxationsverfahrens bei diagonaldominanten Matrizen beweisen.

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Summary In this paper we give a general definition what is meant by total-step-, single-step- and successive relaxation iterative method and we apply these concepts on systems of linear equations. In the special case of a matrix with zero diagonal entries we obtain the well knownJacobi-, Gauss-Seidel- and Relaxation iterative method. Theorem 1 gives conditions for the convergence of the singlestep-iterative method for general, non-negative matrices. The proof is similar to that given byStein andRosenberg in [2] (1948) for a special case. A corollary gives conditions for the convergence of the relaxation-iterative method for non-negative matrices. Further on we prove theorem 2 about the convergence of the relaxation-iterative method with diagonally dominant matrices.

     

The Origins of the Translator's Workstation

The first proposals for various component tools of what is now called the translator's workstation or translator's workbench are traced back to the 1970s and early 1980s in various, often independent, proposals at different stages in the development of computers and in their use by translators.     

From Conditional Events to Conditional Measures: A New Axiomatic Approach

Our starting point is a definition of conditional event EH which differs from many seemingly similar ones adopted in the relevant literature since 1935, starting with de Finetti. In fact, if we do not assign the same third value u (undetermined) to all conditional events, but make it depend on EH, it turns out that this function t(EH) can be taken as a general conditional uncertainty measure, and we get (through a suitable – in a sense, compulsory – choice of the relevant operations among conditional events) the natural axioms for many different (besides probability) conditional measures.     

End-to-end communications management using TMN “X” interfaces

The ongoing integration of LANs and WANs to support global communications and businesses and the emergence of integrated broadband communication services has created an increased demand for cooperation between customers, network and service providers to achieve end-to-end service management. Such a cooperation between autonomous authorities, each defining their own administrative management domains, requires the application of an open standardized framework to facilitate and regulate interworking. Such a framework is given by the ITU-T recommendations on TMN, where the so-called X interface is of particular importance for inter-domain management. In this paper, we explain the role of the TMN X interface within an inter-domain TMN architecture supporting end-to-end communications management. We identify the important issues that need to be addressed for the definition and realization of TMN X interfaces and report about our practical experiences with the implementation of TMN X interfaces in the PREPARE project.     

Unitary immersions of nonlinear systems

In this paper, we define what we call a unitary immersion of a nonlinear system. We observe that, for classical Hamiltonian systems, this notion contains, in some sense, the concept of quantization. We restrict our attention to degree-zero unitary immersions, where all observation functions must be represented by operators of the type multiplication by a function. We show that the problem of classifying such degree-zero unitary immersions of a given nonlinear system is not obvious. In some cases, we solve this problem.Chargé de Recherche au CNRS.Maître de Conférences.     

A Generalization of Jumps and Labels

This paper describes a new language feature that is a hybrid of labels and procedures. It is closely related to jumping out of a functional subroutine, and includes conventional labels and jumping as a special, but probably not most useful, case. It is independent of assignment, ie., it can be added to a purely-functional (non-imperative) system (such as LISP without pseudo-functions or program feature). Experiments in purely functional programming suggest that its main use will be in success/failure situations, and failure actions. This innovation is incorporated in the projected experimental system, ISWIM.     

Choosing reference classes and building provisional models

A well-known problem in default logic is the ability of naive reasoners to explain bothg and ¬g from a set of observations. This problem is treated in at least two different ways within that camp.One approach is examination of the various explanations and choosing among them on the basis of various explanation comparators. A typical comparator is choosing the explanation that depends on the most specific observation, similar to the notion of narrowest reference class.Others examine default extensions of the observations and choose whatever is true in any extension, or what is true in all extensions or what is true in preferred extensions. Default extensions are sometimes thought of as acceptable models of the world that are discarded as more knowledge becomes available.We argue that the notions of specificity and extension lack clear semantics. Furthermore, we show that the problems these ideas were supposed to solve can be handled easily within a probabilistic framework.     

A Full Bayesian Approach to Curve and Surface Reconstruction

When interpolating incomplete data, one can choose a parametric model, or opt for a more general approach and use a non-parametric model which allows a very large class of interpolants. A popular non-parametric model for interpolating various types of data is based on regularization, which looks for an interpolant that is both close to the data and also smooth in some sense. Formally, this interpolant is obtained by minimizing an error functional which is the weighted sum of a fidelity term and a smoothness term.The classical approach to regularization is: select optimal weights (also called hyperparameters) that should be assigned to these two terms, and minimize the resulting error functional.However, using only the optimal weights does not guarantee that the chosen function will be optimal in some sense, such as the maximum likelihood criterion, or the minimal square error criterion. For that, we have to consider all possible weights.The approach suggested here is to use the full probability distribution on the space of admissible functions, as opposed to the probability induced by using a single combination of weights. The reason is as follows: the weight actually determines the probability space in which we are working. For a given weight , the probability of a function f is proportional to exp(– f² _uu du) (for the case of a function with one variable). For each different , there is a different solution to the restoration problem; denote it by f. Now, if we had known , it would not be necessary to use all the weights; however, all we are given are some noisy measurements of f, and we do not know the correct . Therefore, the mathematically correct solution is to calculate, for every , the probability that f was sampled from a space whose probability is determined by , and average the different f's weighted by these probabilities. The same argument holds for the noise variance, which is also unknown.Three basic problems are addressed is this work: Computing the MAP estimate, that is, the function f maximizing Pr(f/D) when the data D is given. This problem is reduced to a one-dimensional optimization problem. Computing the MSE estimate. This function is defined at each point x as f(x)Pr(f/D) f. This problem is reduced to computing a one-dimensional integral.In the general setting, the MAP estimate is not equal to the MSE estimate. Computing the pointwise uncertainty associated with the MSE solution. This problem is reduced to computing three one-dimensional integrals.     

Enhancing the performance of an agent-based manufacturing system through learning and forecasting

Agent-based technology has been identified as an important approach for developing next generation manufacturing systems. One of the key techniques needed for implementing such advanced systems will be learning. This paper first discusses learning issues in agent-based manufacturing systems and reviews related approaches, then describes how to enhance the performance of an agent-based manufacturing system through learning from history (based on distributed case-based learning and reasoning) and learning from the future (through system forecasting simulation). Learning from history is used to enhance coordination capabilities by minimizing communication and processing overheads. Learning from the future is used to adjust promissory schedules through forecasting simulation, by taking into account the shop floor interactions, production and transportation time. Detailed learning and reasoning mechanisms are described and partial experimental results are presented.     

Personalized and Adaptive Services on Board a Car: An Application for Tourist Information

Personalization and adaptation techniques are an interesting opportunity to design new services on-board vehicles. In this context, in fact, the need of an individual user to receive the right service at the right time and in the right way is more critical than in other cases, where personalization and adaptation already showed interesting advantages. At the same time, this context of application can provide new interesting insights for user modeling and adaptation. In the paper we present an architecture for providing personalized services on-board vehicles and we discuss an application to the case of tourist information. We focus on the choices we made to design an on-board system which was as less intrusive and distracting as possible and that could adapt its recommendations, the way it presents them and its own behavior to the user's preferences/interests and to the context of interaction (especially the driving conditions).     

AI & Society and society

This article looks at the broadest implications of public acceptance of AI. A distinction is drawn between conscious belief in a technology, and organic belief where the technology is incorporated into an unconscious world model. The extent to which we feel threatened by AI's apparent denial of spirit is considered, along with a discussion of how people react to this threat. It is proposed that organic acceptance of AI models would lead to a rebirth of popular spiritual concepts as paradoxical as the New Age ideas that have their roots in the theories of physics. Finally the relevance of this speculation is discussed in terms of how it could impinge upon public acceptability of AI technology.     

On the number of Eulerian orientations of a graph

An Eulerian orientation of an undirected Eulerian graph is an orientation of the edges of the graph such that for every vertex the in-degree is equal to the out-degree. Eulerian orientations are natural flow-like structures, and Welsh has pointed out that computing their number corresponds to evaluating the Tutte polynomial at the point (0, –2) [JVW], [Wl], and is further equivalent to evaluating ice-type partition functions in statistical physics [W2]. In this paper we resolve the complexity of counting the number of Eulerian orientations of an arbitrary Eulerian graph.We give an efficient randomized approximation algorithm for counting Eulerian orientations of any Eulerian graph. Our algorithm is based on a reduction to counting perfect matchings for a class of graphs for which the methods of Broder [B], Jerrum and Sinclair [JS1], and others [DL] [DS] apply. A crucial step of the reduction is the Monotonicity Lemma (Lemma 3.1) which is of independent combinatorial interest. Roughly speaking, the Monotonicity Lemma establishes the intuitive fact that increasing the number of constraints applied on a flow problem cannot increase the number of solutions. The proof of the lemma involves a new decomposition technique which decouples problematically overlapping structures (a recurrent obstacle in handling large combinatorial populations) and allows detailed enumeration arguments. As a by-product, we exhibit a class of graphs for which perfect and near-perfect matchings are polynomially related, and hence the permanent can be approximated, for reasons other than short augmenting paths (previously the only known approach).We also give the complementary hardness result, namely, that counting exactly Eulerian orientations is #P-complete. Finally, we provide some connections with counting Euler tours.     

Sometime = always + recursion ≡ always on the equivalence of the intermittent and invariant assertions methods for proving inevitability properties of programs

Summary We propose and compare two induction principles called always and sometime for proving inevitability properties of programs. They are respective formalizations and generalizations of Floyd invariant assertions and Burstall intermittent assertions methods for proving total correctness of sequential programs whose methodological advantages or disadvantages have been discussed in a number of previous papers. Both principles are formalized in the abstract setting of arbitrary nondeterministic transition systems and illustrated by appropriate examples. The sometime method is interpreted as a recursive application of the always method. Hence always can be considered as a special case of sometime. These proof methods are strongly equivalent in the sense that a proof by one induction principle can be rewritten into a proof by the other one. The first two theorems of the paper show that an invariant for the always method can be translated into an invariant for the sometime method even if every recursive application of the later is required to be of finite length. The third and main theorem of the paper shows how to translate an invariant for the sometime method into an invariant for the always method. It is emphasized that this translation technique follows the idea of transforming recursive programs into iterative ones. Of course, a general translation technique does not imply that the original sometime invariant and the resulting always invariant are equally understandable. This is illustrated by an example.     

Recognition of handwritten musical notes by a modified Neocognitron

A neural network for recognition of handwritten musical notes, based on the well-known Neocognitron model, is described. The Neocognitron has been used for the what pathway (symbol recognition), while contextual knowledge has been applied for the where (symbol placement). This way, we benefit from dividing the process for dealing with this complicated recognition task. Also, different degrees of intrusiveness in learning have been incorporated in the same network: More intrusive supervised learning has been implemented in the lower neuron layers and less intrusive in the upper one. This way, the network adapts itself to the handwriting of the user. The network consists of a 13×49 input layer and three pairs of simple and complex neuron layers. It has been trained to recognize 20 symbols of unconnected notes on a musical staff and was tested with a set of unlearned input notes. Its recognition rate for the individual unseen notes was up to 93%, averaging 80% for all categories. These preliminary results indicate that a modified Neocognitron could be a good candidate for identification of handwritten musical notes.     

EOL forms

Summary In this paper the notions of L form and its interpretations are introduced to define families of structurally similar L systems. The families of L systems thus defined are studied from a number of different points of view. It is felt that this novel approach will shed new light on many questions concerning L systems.     

Meaningful Alignments

We propose a method for detecting geometric structures in an image, without any a priori information. Roughly speaking, we say that an observed geometric event is meaningful if the expectation of its occurences would be very small in a random image. We discuss the apories of this definition, solve several of them by introducing maximal meaningful events and analyzing their structure. This methodology is applied to the detection of alignments in images.     

Modelling structures in generic space, a condition for adaptiveness of monitoring cognitive agent

The adaptiveness of agents is one of the basic conditions for the autonomy. This paper describes an approach of adaptiveness forMonitoring Cognitive Agents based on the notion of generic spaces. This notion allows the definition of virtual generic processes so that any particular actual process is then a simple configuration of the generic process, that is to say a set of values of parameters. Consequently, generic domain ontology containing the generic knowledge for solving problems concerning the generic process can be developed. This lead to the design of Generic Monitoring Cognitive Agent, a class of agent in which the whole knowledge corpus is generic. In other words, modeling a process within a generic space becomes configuring a generic process and adaptiveness becomes genericity, that is to say independence regarding technology. In this paper, we present an application of this approach on Sachem, a Generic Monitoring Cognitive Agent designed in order to help the operators in operating a blast furnace. Specifically, the NeuroGaz module of Sachem will be used to present the notion of a generic blast furnace. The adaptiveness of Sachem can then be noted through the low cost of the deployment of a Sachem instance on different blast furnaces and the ability of NeuroGaz in solving problem and learning from various top gas instrumentation.     

A formal model of atomicity in asynchronous systems

Summary We propose a generalisation of occurrence graphs as a formal model of computational structure. The model is used to define the atomic occurrence of a program, to characterise interference freeness between programs, and to model error recovery in a decentralised system.     

The effects of a “distinct window” screen design on computer-mediated group decision making

An experiment was performed to test a distinct-window conferencing screen design as an electronic cue of social status differences in computer-mediated group decision-making. The screen design included one distinct window to symbolize high-status, and two nondistinct windows to symbolize low-status. The results indicated that the distinct-window screen design did produce status affects in groups of peers making decisions on judgmental problems. Randomly assigned occupants of the distinct window had greater influence on group decisions and member's attitudes than occupants of nondistinct windows.The authors would like to thank Shyam Kamadolli and Phaderm Nangsue, the programmers who developed the software used in this experiment. We would also like to thank the editor and our three anonymous reviewers for exceedingly helpful comments on an earlier draft of this article.